Surveys are important tools for gaining information about a subject from a target audience. By surveying a target audience one may learn preferences, viewpoints, opinions, likes and/or dislikes, and/or other information regarding various subjects, such as products, services, brands, political candidates, etc. Traditionally, surveys have been conducted through active solicitation of information from participants. That is, members of a target audience have traditionally been invited to participate in a survey in which the participants are presented questions in order to actively solicit their responses, thereby providing information about their respective viewpoints, opinions, etc. about a given subject, such as a particular product, service, brand, etc.
Traditionally, for a given survey, the target audience to be invited to participate in the survey may be selected randomly or based on certain characteristics they possess, such as their demographics (age, geographic location, family status, etc.), interests, their use or familiarity with a given subject (e.g., certain products, services, etc.), and/or other characteristics. The members of a target audience who participate in a given survey may be referred to generally as “panelists.” In some instances, incentives or rewards are offered to target audience members to encourage their participation in traditional surveys. Traditional surveys generally present questions to members of the target audience (or “panelists”) to actively solicit their responses, and the members' responses are recorded for analysis. The members may be logically grouped in various ways, such as based on certain characteristics of the members like gender, age, education level, geographic location, etc. Thus, surveys may enable insight to be gained by market researchers regarding the views/opinions of the various members of a target audience about a subject.
Various mechanisms have been used for interacting with panelists for conducting traditional surveys. One approach is telephone-based surveys, where a human operator or interactive voice response (“IVR”) system may interact with the panelist to conduct the survey. The panelist's responses are typically recorded to a computer-readable data storage medium for later analysis.
Another approach for conducting surveys has been through online web-based surveys (or “online panels”). In general, panels are an approach to sampling and maintaining contact lists for research by any channel, and such panels have evolved to be implemented online via web-based surveys. When conducting a web-based survey, panelists access and conduct a survey via the Internet, such as through a particular website. A web server hosts a website that presents a user interface to each panelist's web browser that accesses the website. In some implementations, a survey engine resides on a web server (e.g., within a web page) presents an appropriate user interface for interacting with the respondent (e.g., presenting questions and receiving input from the respondent for answering the questions). Thus, in a traditional web-based survey, each panelist interacts with a user interface via their Internet connection with the hosting web server to input responses to the questions, and those responses are recorded to a computer-readable data storage medium for later analysis.
From the collected survey information, various types of market research metrics may be derived reflecting the knowledge (e.g., awareness, opinions, etc.) of the survey participants about the subject of the survey (e.g., a given brand, product, etc.). For instance, one type of survey information that is often collected in a survey is information regarding whether the survey participant would recommend the subject of the survey (e.g., a particular brand, product, etc.) to others. This information is often used to derive a score or metric reflecting how likely survey participants are to recommend the subject of the survey to others. One example of a recommendation metric that is commonly used in the market research industry is known as a Net Promoter® score or NPS® (Net Promoter, NPS, and Net Promoter Score are trademarks of Satmetrix Systems, Inc., Bain & Company, and Fred Reichheld). Typically, the survey actively solicits recommendation information from a participant by asking a question, like “How likely are you to recommend this brand to other people?” The participant is typically offered a scale from 0-10 in which to indicate his/her response. Thus, individual responses can range from 0 (not at all likely to recommend) to 10 (extremely likely to recommend). Responses falling into an upper range of the scale (e.g., responses of 9 and 10) may be referred to as “Promoter” responses, and responses falling into a lower range of the scale (e.g., responses of 0-6) may be referred to as “Detractor” responses. The scores received from a target audience of survey participants in response to the recommendation question may then be transformed into a grouped score that is computed as the percentage of responses falling into the upper range of the scale (e.g., Promoter responses) and then subtracting the percentage of responses falling into a lower range of the scale (e.g., Detractor responses).
The resulting metric or scores typically range from −100 to +100. A subject (e.g., brand, product, etc.) that gets perfect Promoter scores (e.g., all responses categorized as Promoter responses) receives a score of 100, and a subject that gets poor scores (e.g., all responses categorized as Detractor responses) ends up with a −100. So, a recommendation metric, such as the type computed in the above-described manner, may provide a single number that is often used in the market research industry to describe how likely survey participants are to recommend a given subject (e.g., brand, product, etc.).